Work Related Stress, Well-Being and Cardiovascular Risk among Flight Logistic Workers: An Observational Study

Abstract

Work-related stress is a known occupational hazard, with a putative role on the development of cardiovascular diseases (CVD). Although several investigations have explored the association in various workplace scenarios, none have focused on the airport flight logistic support personnel, a transportation business of crucial importance, potentially exposed to job stress and consequently to an increase in CVD risk. We explored the relationship between work-related stress and cardiovascular risk in 568 healthy workers of a flight logistic support company using the Health and Safety Executive questionnaire, the Framingham Heart Study General Cardiovascular Disease (CVD) Risk Prediction Score, and the WHO general well-being index (WHO-5). We used univariate and multivariate statistical methods to take account of possible confounders. Our results show that a low job support significantly increases the CVD risk score and decreases the WHO well-being index with reference to subjects reporting high support on the job. In addition, the well-being index of workers with high strain jobs appears lower in respect to workers employed in low strain job. The multivariate analysis confirms a protective effect of job support, and shows a detrimental influence on CVD risk by physical inactivity, regular intake of alcohol, and a low educational level. In addition, job control, job support, low strain, and high demand coupled with high control (active job) showed a beneficial effect on psychological well-being. Our results suggest that a combination of general risk factors and organizational factors contributes to increase CVD risk and well-being, representing a crucial target for intervention strategies to promote health in the workplace.

The Dark and the Light Side of the Expatriate’s Cross-Cultural Adjustment: A Novel Framework Including Perceived Organizational Support, Work Related Stress and Innovation

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Correction Workers’ Burnout and Outcomes: A Bayesian Network Approach

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